Evidence map›Paper›PMID 33428733›Full record

ArticleThe Journal of chiropractic education2021

Exploring the application of the Charlson Comorbidity Index to assess the patient population seen in a Veterans Affairs chiropractic residency program.

Vivian T Ly, Brian C Coleman, Christopher M Coulis, Anthony J Lisi

Open access · diamondAbstract read
In one paragraph

Article in The Journal of chiropractic education, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 100% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Vivian T Ly
Brian C Coleman
Christopher M Coulis
Anthony J Lisi

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

objectiveChiropractic trainees require exposure to a diverse patient base, including patients with multiple medical conditions. The Veterans Affairs (VA) Chiropractic Residency Program aims for its doctor of chiropractic (DC) residents to gain experience managing a range of multimorbid cases, yet to our knowledge there are no published data on the comorbidity characteristics of patients seen by VA DC residents. We tested 2 approaches to obtaining Charlson Comorbidity Index (CCI) scores and compared CCI scores of resident patients with those of staff DCs at 1 VA medical center.

methodsTwo processes of data collection to calculate CCI scores were developed. Time differences and agreement between methods were assessed. Comparison of CCI distribution between resident DC and staff DCs was done using 100 Monte Carlo simulation iterations of Fisher's exact test.

resultsBoth methods were able to calculate CCI scores (n = 22). The automated method was faster than the manual (13 vs 78 seconds per patient). CCI scores agreement between methods was good (κ = 0.67). We failed to find a significant difference in the distribution of resident DC and staff DC patients (mean p = .377; 95% CI, .375-.379).

conclusionCCI scores of a VA chiropractic resident's patients are measurable with both manual and automated methods, although automated may be preferred for its time efficiency. At the facility studied, the resident and staff DCs did not see patients with significantly different distributions of CCI scores. Applying CCI may give better insight into the characteristics of DC trainee patient populations.

Indexed as

ChiropracticComorbidityEducationResidencyVeterans

Identifiers

PMID33428733
PMCPMC8528440
OpenAlexW3119148110

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.